The focus of this project is the development of appropriate statistical methodologies for analysis of molecular genetic data from a variety of biologic systems. Investigations continued into the modeling and analysis of data from developmental toxicity experiments, with specific attention directed at the dominant lethal assay in the male mouse. Of interest is identification of the sampling distribution of various endpoints from such experiment. A large control database was assembled, from which sampling characteristics of the endpoints interest were determined. Statistical methods for analyzing data conforming these characteristics require minimal assumptions on the distribution of the response; these include bootstrapping, quasi-likelihood methods, and other distribution-free analyses. These were compared to identify which of the methods provide optimal statistical characteristics, such as minimal type 1 error, a maximal power. Investigations were also begun into the examination and analysis of genetic susceptibility in animal and human subjects. Statistical models a methods were identified for assessing gene-environment interactions; these include logistic regression and other generalized linear models.